An e-commerce company processes substantial volumes of consumer behavior data stored in HDFS by leveraging Apache Spark on Amazon EMR. This task is performed daily, and the volume of data exhibits significant seasonal fluctuations, notably spiking during holidays and major sales events. What is the most cost-effective strategy to manage these variable demands without risking data loss or the need to terminate the entire cluster?